Results 81 to 90 of about 1,195,838 (307)

Pharmacological chromatin remodeling enhances response to estrogen therapy in ER+ breast cancer

Molecular Oncology, EarlyView.
Estrogen therapy elicits clinical benefit in ~ 30% of patients with endocrine‐resistant estrogen receptor (ER)‐positive breast cancer. Based on findings that ER transcriptional activation underlies response to estrogen therapy, we tested the effects of epigenetic dysregulation via pharmacological inhibition of histone deacetylases (HDACi).
Anneka L. Johnson Thomas, Barbara Karakyriakou, Patricia C. Muskus, Alyssa M. Roberts, Justin Rendleman, Alexa Warren, Hanxu Lu, Kimberly A. Birmingham, Malone K. Friedman, Abigail E. Goen, Huijuan Yang, Owen M. Wilkins, Fred W. Kolling, Eugene Demidenko, Julie M. Jorns, Brock C. Christensen, Todd W. Miller   +16 more
wiley   +1 more source

Machine Learning Approaches for Subcluster in IoT Sensor Networks with Hierarchical Clustering and Dendrograms

Emitter: International Journal of Engineering Technology
This research focuses on optimizing IoT Sensor Networks (ISNs) by implementing hierarchical clustering algorithms. Traditional clustering methods often lead to imbalanced energy consumption, impacting network lifetime and performance.
Fuad Bajaber
doaj   +1 more source

Tree Structured Dirichlet Processes for Hierarchical Morphological Segmentation [PDF]

Computational Linguistics, 2018
This article presents a probabilistic hierarchical clustering model for morphological segmentation. In contrast to existing approaches to morphology learning, our method allows learning hierarchical organization of word morphology as a collection of tree
Burcu Can, Suresh Manandhar
doaj   +1 more source

Spatial biology in cancer epigenetics

Molecular Oncology, EarlyView.
Spatial epigenomics combines molecular profiling with tissue architecture to reveal how gene regulation is organized within intact tissues. In cancer, these technologies uncover the mechanisms driving tumor heterogeneity and microenvironmental interactions, opening new opportunities for biomarker discovery and precision medicine.
Eva Crespo‐García, Manel Esteller
wiley   +1 more source

Hierarchical kernel spectral clustering [PDF]

Neural Networks, 2012
Kernel spectral clustering fits in a constrained optimization framework where the primal problem is expressed in terms of high-dimensional feature maps and the dual problem is expressed in terms of kernel evaluations. An eigenvalue problem is solved at the training stage and projections onto the eigenvectors constitute the clustering model.
Alzate Perez, Carlos, Suykens, Johan
openaire   +4 more sources

Aggregation of Individual Feature Based Similarities and Application to Hierarchical Clustering

Chemical Engineering Transactions, 2015
The measure of similarity/dissimilarity is important to clustering algorithms. By using different similarity metrics, a clustering algorithm may achieve different clustering results.
N. Zhou, B.J. Xie, T. Wang
doaj   +1 more source

A Cooperative Binary-Clustering Framework Based on Majority Voting for Twitter Sentiment Analysis

IEEE Access, 2020
Twitter sentiment analysis is a challenging problem in natural language processing. For this purpose, supervised learning techniques have mostly been employed, which require labeled data for training.
Maryum Bibi, Wajid Aziz, Majid Almaraashi, Imtiaz Hussain Khan, Malik Sajjad Ahmed Nadeem, Nazneen Habib   +5 more
doaj   +1 more source

The VHL tumor suppressor at the crossroad of protein folding, aggregation, and cancer

Molecular Oncology, EarlyView.
Mutations, environmental stress, and chaperone dysfunction can destabilize pVHL, promoting its conversion from the native folded state into amyloid‐like assemblies. This transition may contribute to protein storage, cell dormancy, survival, and drug resistance.
Lara Abad, Silvio Carlo Ermanno Tosatto, Emanuela Leonardi   +2 more
wiley   +1 more source

Statistical Significance for Hierarchical Clustering [PDF]

Biometrics, 2017
Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high-dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure.
Kimes, Patrick K., Liu, Yufeng, Hayes, David Neil, Marron, James Stephen   +3 more
openaire   +3 more sources

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source